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Related Experiment Video

Updated: Mar 31, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
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A Design Pattern for Decentralised Decision Making.

Andreagiovanni Reina1, Gabriele Valentini1, Cristian Fernández-Oto2

  • 1IRIDIA, Université Libre de Bruxelles, Brussels, Belgium.

Plos One
|October 27, 2015
PubMed
Summary
This summary is machine-generated.

We present a design pattern for collective decision-making in large-scale systems, inspired by honeybee swarm behavior. This pattern bridges microscopic implementation with macroscopic predictions, enhancing decentralized system engineering.

Related Experiment Videos

Last Updated: Mar 31, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
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The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

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Area of Science:

  • Complex Systems Engineering
  • Swarm Intelligence
  • Collective Behavior

Background:

  • Engineering large-scale decentralized systems demands methodologies linking microscopic implementation to macroscopic behavior.
  • Existing general-purpose methodologies are limited; specific design patterns address classes of problems.
  • Honeybee swarm nest-site selection offers a model for understanding consensus in decentralized systems.

Purpose of the Study:

  • Propose a design pattern for collective decision-making in decentralized systems.
  • Provide formal guidelines for microscopic implementation to match macroscopic predictions.
  • Enhance understanding of decision-making in natural and engineered systems.

Main Methods:

  • Grounded the design pattern on experimental and theoretical studies of honeybee (Apis mellifera) swarm behavior.
  • Developed formal guidelines for microscopic implementation of collective decisions.
  • Discussed implementation strategies for homogeneous and heterogeneous multiagent systems.
  • Incorporated spatial and topological factors influencing the micro-macro link.

Main Results:

  • Formalized a design pattern for collective decision-making.
  • Demonstrated quantitative matching of microscopic implementation to macroscopic predictions.
  • Showcased the pattern's viability through two case studies.
  • Provided methods to address spatial and topological influences.

Conclusions:

  • The proposed design pattern enables robust engineering of large-scale decentralized systems.
  • The approach facilitates deeper understanding of natural collective decision-making, including heterogeneity and spatial factors.
  • This pattern offers a transferable methodology for complex system design and analysis.